Wait. So for each unique condition in the experiment you only have 1 observation per subject? You can’t fit a hierarchical model to that kind of data (well, you can, but the measurement noise term will be completely determined by the prior). I don’t know how to set up non-hierarchical repeated measures in brms, but for plain old Stan see my lectures and code.
(Edit: and just to clarify, I guess I’m making the assumption that you asked brms to model the data hierarchically from your terminology; usually when folks talk about random intercepts and slopes, they’re talking about a hierarchical model)